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OpenTelemetry LLM tracing

Send OpenTelemetry traces to an LLM-aware dashboard

Currai ingests OTLP traces and turns model calls, tools, retrievers, tokens, cost, and latency into LLM observability views your team can use.

Primary keyword

OpenTelemetry LLM tracing

Currai covers

Traces, generations, spans, evals, prompt A/B tests, token usage, cost, latency, sessions, users, and OpenTelemetry ingestion.

Keep your instrumentation, add LLM context

OpenTelemetry is the standard way to move traces across services. Currai accepts OTLP/HTTP so teams can send traces from existing OpenTelemetry exporters while getting views designed for LLM apps.

That means prompts, completions, model attributes, usage, latency, and nested spans remain connected in one trace.

  • Export OTLP traces directly to Currai.
  • Map GenAI semantic attributes into Currai generations and spans.
  • Use OpenTelemetry from languages beyond Python and TypeScript.

For services that already use OTel

If your backend already has OpenTelemetry, Currai can receive LLM traces without forcing a separate tracing stack. Point the exporter at Currai and keep your service-level instrumentation strategy intact.

Questions about OpenTelemetry LLM tracing

Can Currai ingest OTLP traces?

Yes. Currai exposes an OTLP/HTTP ingestion endpoint for OpenTelemetry traces.

Do I need the Currai SDK if I use OpenTelemetry?

No. The SDK is convenient for Python and TypeScript, but OpenTelemetry lets any compatible service export traces to Currai.